Electromagnetic inversion for biomedical imaging, antenna characterization, and sea ice remote sensing applications

Firoozy, Nariman; Bayat, Nozhan; Brown, Thomas J.; Narendra, Chaitanya; Mojabi, Puyan; Niu, Chen; Tiede, Tyler; Neusitzer, Thomas; Li, Xiang; Jeffrey, Ian; LoVetri, Joe; Barber, David G.

doi:10.1109/ursiap-rasc.2016.7601406

Cited by 9 publications

(11 citation statements)

References 29 publications

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“…These parameters are the relative permittivity (dielectric constant) and the conductivity of the object, often represented by the complex-valued permittivity variableε r , and it is these frequency-dependent properties that allow qualitative and quantitative differentiation of biological tissue types, including potential malignancies. Conventionally it has been assumed that the bulk-magnetic Microwave imaging is a non-destructive imaging modality which can be used for various applications, including biomedical imaging, industrial non-destructive testing, and remote sensing [6][7][8][9][10][11][12][13][14][15][16][17]. Breast imaging in the context of cancer detection, however, has been the primary focus and consequentially the most developed application of the technology in the biomedical field.…”

Section: Contributionsmentioning

confidence: 99%

Enhanced Detection of Magnetic Nanoparticles Using a Novel Microwave Ferromagnetic Resonance Imaging System

Kaye

Gilmore

LoVetri

2021

IEEE Trans. Biomed. Eng.

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Although microwave imaging (MWI) remains a promising future diagnostic tool in breast cancer detection and monitoring, its progress towards widespread clinical application would greatly benefit from an improvement to its relatively low spatial and contrast resolution in delineating healthy and abnormal tissues, especially in comparison to established modalities such as mammography and magnetic resonance imaging (MRI). To this end, research has been undertaken in this work exploring multiple methods of improving the quality of MWI reconstructions.

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Section: Contributionsmentioning

confidence: 99%

Enhanced Detection of Magnetic Nanoparticles Using a Novel Microwave Ferromagnetic Resonance Imaging System

Kaye

Gilmore

LoVetri

2021

IEEE Trans. Biomed. Eng.

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“…There are two general categories of EM inverse problems: inverse scattering problems, and inverse source problems. The former is used to determine unknown objects (e.g., medical imaging problems [18]), while the latter is used to determine the electromagnetic sources of an unknown active source (e.g., near-field antenna measurements [18]). For the SAR characterization problem, we use the inverse source framework to determine the effective DUT currents in the presence of the known phantom.…”

Section: Motivation For Researchmentioning

confidence: 99%

“…The unregularized solution also changes significantly, but this makes sense since there is a noise variance with respect to nearby equations which are also subparallel. 18 Nonetheless, with a choice of λ C = 2.6 × 10 −2 , the simultaneous inversion solution is relatively stable. The unbalanced substitution solution is also relatively good (but still worse than the SI method).…”

Section: Factormentioning

confidence: 99%

Electromagnetic Inversion for Noninvasive Specific Absorption Rate Characterization

Phaneuf

Mojabi

2020

IEEE J. Electromagn. RF Microw. Med. Biol.

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“…Electromagnetic inversion is the process by which specific properties of an investigation domain are calculated from electromagnetic data obtained outside that investigation domain; the properties of interest are also a cause (or part of the cause) for the measured electromagnetic data (the effect) [2,14]. 8 The properties of interest, investigation domain, and type of electromagnetic data can vary depending on the application.…”

Section: Electromagnetic Inversionmentioning

confidence: 99%

“…Electromagnetic inverse problems can be separated into two different types based on the property of interest: (I) inverse source problems, and (II) inverse scattering problems. In (I) sources that generate specific electromagnetic data are the property of interest (e.g., seeking an equivalent current distribution in antenna diagnostics or contrast sources in microwave imaging [14,19]). Therefore, inverse source problems are formulated as…”

Section: Types Of Electromagnetic Inverse Problemsmentioning

confidence: 99%

Multi-Plane Magnetic Near-Field Data Inversion Using the Source Reconstruction Method

Narendra

Brown

Bayat

et al. 2018

2018 18th International Symposium on Antenna Technology and Applied Electromagnetics (ANTEM)

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In this work, we use the electromagnetic inversion (EI) framework to develop/improve algorithms for the purpose of antenna design and characterization. Broadly speaking, antennas are any device, object, or system that can transform energy in the form of guided waves to energy in the form of radiated waves in space. In our increasingly wireless technology landscape, many different types of antennas are being analyzed and developed for a variety of applications. Therefore a flexible design/characterization methodology is required to support our future wireless engineering needs.To this end, we employ an EI methodology that allows the flexibility to develop novel antenna characterization and design algorithms in a variety of applications. In general, electromagnetic inversion enables the determination of an electromagnetic property of interest (e.g., relative permittivity or equivalent current distribution) in an investigation domain by processing some type of electromagnetic data (e.g., complex electric field, phaseless data, or far-field performance criteria) on a separate measurement/desired data domain wherein the investigation and data domains can be arbitrarily shaped; our methodology allows for this flexibility to be utilized. Through the use of this methodology and the electromagnetic surface and volume equivalence principles we develop EI algorithms to contribute to the areas of metasurface design, microwave imaging, and dielectric lens/antenna design. Specifically, (i) we develop and demonstrate a gradient-based EI algorithm that can directly design the circuit admittance profiles of metasurfaces from desired complex or phaseless (magnitude-only) magnetic field data on an external data domain, (ii) we develop and verify inverse scattering algorithms to reconstruct dielectric profiles from phaseless synthetic and experimentally measured data, and finally (iii) we introduce a combined inverse source and scattering technique to tailor electromagnetic fields by designing passive, lossless, and reflectionless dielectric profiles to transform an existing electromagnetic field distribution from a known feed to one that satisfies desired far-field performance criteria such as main beam directions, null locations, and half-power beamwidth. First, I would like thank my advisor and friend Dr. Puyan Mojabi for his guidance throughout my academic journey and for inspiring me to begin the journey in the first place all those years ago in his antennas course at the end of my B.Sc. Thanks also to my friends and colleagues Dr. Trevor Brown, Chen Niu, and Dr. Nozhan Bayat for making my time at the University of Manitoba an absolute joy. I would like to express my gratitude to my Ph.D. internal committee members Dr. Ian Jeffrey, Dr. Jason Fiege, and my external committee member Dr. Andrea Massa for taking the time to help me improve my thesis. Lastly, I'd like to thank the

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Electromagnetic inversion for biomedical imaging, antenna characterization, and sea ice remote sensing applications

Cited by 9 publications

References 29 publications

Enhanced Detection of Magnetic Nanoparticles Using a Novel Microwave Ferromagnetic Resonance Imaging System

Enhanced Detection of Magnetic Nanoparticles Using a Novel Microwave Ferromagnetic Resonance Imaging System

Electromagnetic Inversion for Noninvasive Specific Absorption Rate Characterization

Multi-Plane Magnetic Near-Field Data Inversion Using the Source Reconstruction Method

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